A Comprehensive Multibody Model of a Collaborative Robot to Support Model-Based Health Management

Autor: Andrea Raviola, Roberto Guida, Antonio Carlo Bertolino, Andrea De Martin, Stefano Mauro, Massimo Sorli
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Robotics, Vol 12, Iss 3, p 71 (2023)
Druh dokumentu: article
ISSN: 2218-6581
DOI: 10.3390/robotics12030071
Popis: Digital models of industrial and collaborative manipulators are widely used for several applications, such as power-efficient trajectory definition, human–robot cooperation safety improvement, and prognostics and health management (PHM) algorithm development. Currently, models with simplified joints present in the literature have been used to evaluate robot macroscopic behavior. However, they are not suitable for the in-depth analyses required by those activities, such as PHM, which demand a punctual description of each subcomponent. This paper aims to fill this gap by presenting a high-fidelity multibody model of a UR5 collaborative robot, containing an accurate description of its full dynamics, electric motors, and gearboxes. Harmonic reducers were described through a translational equivalent lumped parameter model, allowing each constitutive element of the reducer to have its decoupled dynamics and mating forces through non-linear penalty contact models. To conclude, both the mathematical model and the real robot on a test rig were tested with a set of different trajectories. The experimental results highlight the ability of the proposed model to accurately replicate joint angular rotation, speed and torques in a wide range of operational scenarios. This research provides the basis for the development of a model-based PHM-oriented framework to carry out detailed and advanced analyses on the effects of manipulator degradations.
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